Analysis of factors that indicated surgery in 400 patients submitted to a complete diagnostic workup for obstructed defecation syndrome and rectal prolapse using a supervised machine learning algorithm.

Journal: Techniques in coloproctology
PMID: 38918256

Abstract

BACKGROUND: Patient selection is extremely important in obstructed defecation syndrome (ODS) and rectal prolapse (RP) surgery. This study assessed factors that guided the indications for ODS and RP surgery and their specific role in our decision-making process using a machine learning approach.

Authors

  • A A Marra
    Proctology Unit, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Largo A. Gemelli, 8, 00168, Rome, Italy.
  • I Simonelli
    Biostatistical Service, Clinical Trial Center, Isola Tiberina - Gemelli Isola Hospital, Rome, Italy.
  • A Parello
    Proctology Unit, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Largo A. Gemelli, 8, 00168, Rome, Italy.
  • F Litta
    Proctology Unit, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Largo A. Gemelli, 8, 00168, Rome, Italy.
  • V De Simone
    Proctology Unit, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Largo A. Gemelli, 8, 00168, Rome, Italy.
  • P Campennì
    Proctology Unit, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Largo A. Gemelli, 8, 00168, Rome, Italy.
  • C Ratto
    Proctology Unit, Fondazione Policlinico Universitario Agostino Gemelli IRCCS, Largo A. Gemelli, 8, 00168, Rome, Italy. carloratto@tiscali.it.

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